The monitoring of intruders usually employs some form of unattended ground sensor (UGS). These sensors can be different depending on their intended application. For example, seismic/acoustic sensors can take advantage of changes of the vibratory seismic motion in the ground and/or sound field resulting from an intruder. Differences in the magnetic field due to ferrous metals can be detected by magnetic sensors. Infrared sensors can detect changes due to a passing heat source. Video and still image systems can be used for a positive visual identification. These different systems are typically used for detecting and monitoring intruder movements, obtaining bearing information and identification.
In the conventional art, seismic/acoustic sensors have been used for many years to monitor the movements of targets in the battlefield. These systems are traditionally used to detect large targets such as troops, wheeled vehicles, and tanks. In more recent years, the significance of the seismic/acoustic sensors have grown as applications have increased to include smaller targets on remote foot paths, the protection of military installations/checkpoints, immigration control on geographical borders, monitoring of airfields, vehicle traffic on roads and highways, etc.
While simply detecting an intruder with a seismic sensor can be fairly straightforward with a strong signature, separating the signature of a stealthy intruder from noise can be very difficult. Often, some sort of confirmation is needed when the detection is made with these seismic signatures. For example, this confirmation can involve turning on cameras with high power consumption or the deployment of personnel to investigate the signature. In either case, the costs can be considerable for false detections.
Intruder systems typically employ a range of methodologies from simple threshold detection to more complex identification logic. Simple threshold approaches that detect intruders immediately after the threshold is exceeded are unacceptable because they frequently lead to false alarms and/or stealthy intruders eluding detection. Furthermore, frequency and time-frequency domain approaches have been proposed; however, they are highly computational. Other high performance identification methods such as matched pursuits or relevance vector machines (RVM) have also been proposed, but the computational nature of these methods is not consistent with the low power requirement for long duration deployments.
Accordingly, there remains a need for a method and system for detecting and identifying intruder activity from seismic vibratory motion that solves the problems of previous detection devices by: (1) providing a system with high sensitivity to detect stealthy targets; (2) maintaining a low false alarm rate; (3) distinguishing between the signatures of different intruders for identification; (4) implementing an approach that is simple so that power consumption is very low; (5) employing a method that is adaptable to different and changing noise environments; and (6) providing a simple and automated deployment procedure.